Abstract
Flow stress behavior of AA5086 was determined using tensile testing at different temperatures from room temperature to 500 °C and strain rates varying between 0.002 and 1 s−1. The strain rate sensitivity parameter and occurrence of dynamic strain aging were then investigated in which an Arrhenius-type model was employed to study the serrated flow. Additionally, hot deformation behavior at temperatures higher than 320 °C was evaluated utilizing hyperbolic-sine constitutive equation. Finally, a feed forward artificial neural network model with back propagation learning algorithm was proposed to predict flow stress for all deformation conditions. The results demonstrated that the strain rate sensitivity at temperature range of 25-270 °C was negative due to occurrence of dynamic strain aging leading to significant reduction in fracture strain. The serrated yielding activation energy was found to be 46.1 kJ/mol. It indicated that the migration of Mg-atoms could be the main reason for this phenomenon. The hot deformation activation energy of AA5086 was also calculated about 202.3 kJ/mol while the dynamic recovery was the main softening process. Moreover, the ANN model having two hidden layers was shown to be an efficient structure for determining flow stress of the examined alloy for all temperatures and strain rates.
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Asgharzadeh, A., Jamshidi Aval, H. & Serajzadeh, S. A Study on Flow Behavior of AA5086 Over a Wide Range of Temperatures. J. of Materi Eng and Perform 25, 1076–1084 (2016). https://doi.org/10.1007/s11665-016-1927-5
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DOI: https://doi.org/10.1007/s11665-016-1927-5